Use of the q-Gaussian mutation in evolutionary algorithms

This paper proposes the use of the q -Gaussian mutation with self-adaptation of the shape of the mutation distribution in evolutionary algorithms. The shape of the q -Gaussian mutation distribution is controlled by a real parameter q . In the proposed method, the real parameter q of the q -Gaussian...

Full description

Saved in:
Bibliographic Details
Published in:Soft computing (Berlin, Germany) Germany), 2011-08, Vol.15 (8), p.1523-1549
Main Authors: Tinós, Renato, Yang, Shengxiang
Format: Article
Language:English
Subjects:
Adaptation
Artificial Intelligence
Computational Intelligence
Control
Engineering
Entropy
Evolutionary algorithms
Experiments
Genetic algorithms
Histograms
Mathematical Logic and Foundations
Mechatronics
Mutation
Normal distribution
Optimization
Original Paper
Parameters
Probability
Robotics
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper proposes the use of the q -Gaussian mutation with self-adaptation of the shape of the mutation distribution in evolutionary algorithms. The shape of the q -Gaussian mutation distribution is controlled by a real parameter q . In the proposed method, the real parameter q of the q -Gaussian mutation is encoded in the chromosome of individuals and hence is allowed to evolve during the evolutionary process. In order to test the new mutation operator, evolution strategy and evolutionary programming algorithms with self-adapted q -Gaussian mutation generated from anisotropic and isotropic distributions are presented. The theoretical analysis of the q -Gaussian mutation is also provided. In the experimental study, the q -Gaussian mutation is compared to Gaussian and Cauchy mutations in the optimization of a set of test functions. Experimental results show the efficiency of the proposed method of self-adapting the mutation distribution in evolutionary algorithms.
ISSN:1432-7643
1433-7479
DOI:10.1007/s00500-010-0686-8